Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "156"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 156 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 30 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 28 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 156, Node N12:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459845 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.453959 3.708216 -0.509910 -0.562281 -0.467543 10.479349 0.332234 40.650747 0.6946 0.7023 0.3874 0.000000 0.000000
2459844 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.353088 2.486859 -1.043422 -0.421753 0.770827 -0.809604 -0.529514 0.576241 0.0288 0.0269 0.0013 nan nan
2459842 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.573277 -0.443147 -0.610087 0.731366 0.116556 0.919530 0.111002 3.767862 0.7385 0.6406 0.2901 6.111266 5.012100
2459841 digital_ok 100.00% 100.00% 100.00% 0.00% - - 2.716925 2.782091 -0.484211 -0.336586 -1.087643 49.030357 0.859700 2.089224 0.0284 0.0263 0.0015 nan nan
2459840 digital_ok 100.00% 100.00% 100.00% 0.00% - - 388.858850 291.489197 102.116939 101.920447 1080.086909 1654.532582 2476.727870 3348.311388 0.0201 0.0172 0.0023 nan nan
2459839 digital_ok 100.00% - - - - - 62.435588 62.749798 219.241410 217.558375 440.500002 384.179307 2875.815010 2847.775904 nan nan nan nan nan
2459838 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.025903 11.813566 0.772385 -0.022132 -0.585038 21.223405 0.476550 20.162731 0.6652 0.5910 0.3861 0.000000 0.000000
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0342 0.0331 0.0009 nan nan
2459835 digital_ok 100.00% 100.00% 100.00% 0.00% - - -0.645984 -0.356256 -1.065332 -0.633777 0.021167 0.310236 -0.505089 6.734077 0.0331 0.0330 0.0013 nan nan
2459833 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.207495 -0.028834 -0.990879 -0.580268 -0.775648 -0.874744 -0.506989 1.919162 0.0308 0.0294 0.0015 nan nan
2459832 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.849687 0.351395 0.435954 0.001946 -0.701442 -0.381714 3.274651 10.051129 0.7532 0.4542 0.5523 4.596113 3.602425
2459831 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.030021 0.534238 -1.041723 0.982812 -0.253394 -0.269665 -0.280008 -1.218551 0.0317 0.0272 0.0015 nan nan
2459830 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.104041 0.841765 1.217076 -0.085767 0.054273 1.088563 8.595457 20.398676 0.7539 0.4728 0.5322 5.612105 5.091596
2459829 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.352879 0.232418 0.876645 -0.253642 -0.140515 0.701644 3.708576 32.507356 0.6855 0.5937 0.3956 16.139110 20.148276
2459828 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.715442 1.004720 0.914386 -0.180091 0.558388 -0.059372 -0.193088 30.198214 0.7475 0.4727 0.5163 0.000000 0.000000
2459827 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.055308 17.391039 2.065325 0.867784 -0.463670 30.361414 1.939803 46.925211 0.0539 0.0789 0.0037 23.097632 21.962288
2459826 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.357817 0.423599 1.516251 -0.161969 1.151882 0.433350 8.680598 18.048588 0.0542 0.0636 0.0050 0.000000 0.000000
2459825 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.423114 23.031817 0.603902 3.056723 0.094292 16.056795 0.150680 20.459276 0.0487 0.0743 0.0052 0.965397 0.959155
2459824 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.144105 0.244328 0.853202 0.154709 0.814004 9.378045 3.017654 15.239454 0.0492 0.0632 0.0031 18.631819 30.937458
2459823 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.541414 1.639187 1.585672 0.120993 0.684026 -0.442509 1.236058 10.564194 0.0484 0.0537 0.0043 95.051216 39.260636
2459822 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.115596 1.582600 1.419967 -0.094285 -0.261056 -0.541950 5.310340 2.557242 0.0655 0.0650 0.0089 1.279868 1.282884
2459821 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.380920 0.283977 1.489177 -0.499914 -0.146665 -0.575256 1.582405 0.655297 0.0475 0.0453 0.0035 1.242938 1.242353
2459820 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.003980 -0.141186 1.603718 -0.483816 1.029771 6.645444 4.550922 24.625111 0.0469 0.0601 0.0046 1.280986 1.278030
2459817 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.060192 1.127719 0.837683 -0.287580 -0.539741 -0.976367 0.555104 1.473618 0.0634 0.0633 0.0059 1.224696 1.223105
2459816 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.591832 20.653869 1.208053 3.634595 0.325896 17.104702 11.162585 49.797782 0.8508 0.4864 0.6112 5.514842 4.598162
2459815 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.694582 1.494820 0.892947 0.169721 -0.493406 0.329905 6.593569 15.884047 0.7950 0.6348 0.5320 5.385873 5.048526
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 156: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 40.650747 3.708216 0.453959 -0.562281 -0.509910 10.479349 -0.467543 40.650747 0.332234

Antenna 156: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Shape 2.486859 -0.353088 2.486859 -1.043422 -0.421753 0.770827 -0.809604 -0.529514 0.576241

Antenna 156: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 3.767862 -0.573277 -0.443147 -0.610087 0.731366 0.116556 0.919530 0.111002 3.767862

Antenna 156: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Variability 49.030357 2.716925 2.782091 -0.484211 -0.336586 -1.087643 49.030357 0.859700 2.089224

Antenna 156: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 3348.311388 388.858850 291.489197 102.116939 101.920447 1080.086909 1654.532582 2476.727870 3348.311388

Antenna 156: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok ee Temporal Discontinuties 2875.815010 62.749798 62.435588 217.558375 219.241410 384.179307 440.500002 2847.775904 2875.815010

Antenna 156: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Variability 21.223405 11.813566 -0.025903 -0.022132 0.772385 21.223405 -0.585038 20.162731 0.476550

Antenna 156: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 6.734077 -0.356256 -0.645984 -0.633777 -1.065332 0.310236 0.021167 6.734077 -0.505089

Antenna 156: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 1.919162 -0.028834 0.207495 -0.580268 -0.990879 -0.874744 -0.775648 1.919162 -0.506989

Antenna 156: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 10.051129 0.849687 0.351395 0.435954 0.001946 -0.701442 -0.381714 3.274651 10.051129

Antenna 156: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Power 0.982812 -0.030021 0.534238 -1.041723 0.982812 -0.253394 -0.269665 -0.280008 -1.218551

Antenna 156: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 20.398676 1.104041 0.841765 1.217076 -0.085767 0.054273 1.088563 8.595457 20.398676

Antenna 156: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 32.507356 0.232418 0.352879 -0.253642 0.876645 0.701644 -0.140515 32.507356 3.708576

Antenna 156: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 30.198214 1.004720 0.715442 -0.180091 0.914386 -0.059372 0.558388 30.198214 -0.193088

Antenna 156: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 46.925211 0.055308 17.391039 2.065325 0.867784 -0.463670 30.361414 1.939803 46.925211

Antenna 156: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 18.048588 0.423599 0.357817 -0.161969 1.516251 0.433350 1.151882 18.048588 8.680598

Antenna 156: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Shape 23.031817 23.031817 0.423114 3.056723 0.603902 16.056795 0.094292 20.459276 0.150680

Antenna 156: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 15.239454 0.144105 0.244328 0.853202 0.154709 0.814004 9.378045 3.017654 15.239454

Antenna 156: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 10.564194 1.639187 1.541414 0.120993 1.585672 -0.442509 0.684026 10.564194 1.236058

Antenna 156: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok ee Temporal Discontinuties 5.310340 1.115596 1.582600 1.419967 -0.094285 -0.261056 -0.541950 5.310340 2.557242

Antenna 156: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok ee Temporal Discontinuties 1.582405 0.283977 0.380920 -0.499914 1.489177 -0.575256 -0.146665 0.655297 1.582405

Antenna 156: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 24.625111 -0.003980 -0.141186 1.603718 -0.483816 1.029771 6.645444 4.550922 24.625111

Antenna 156: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 1.473618 1.060192 1.127719 0.837683 -0.287580 -0.539741 -0.976367 0.555104 1.473618

Antenna 156: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 49.797782 20.653869 0.591832 3.634595 1.208053 17.104702 0.325896 49.797782 11.162585

Antenna 156: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Temporal Discontinuties 15.884047 1.494820 1.694582 0.169721 0.892947 0.329905 -0.493406 15.884047 6.593569

Antenna 156: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 156: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
156 N12 digital_ok nn Shape nan nan nan inf inf nan nan nan nan
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